Instructions to use dmitchelljackson/cerebellum-e4b-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dmitchelljackson/cerebellum-e4b-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-4-E4B-it") model = PeftModel.from_pretrained(base_model, "dmitchelljackson/cerebellum-e4b-lora") - Notebooks
- Google Colab
- Kaggle
File size: 361 Bytes
aa15c60 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | {
"base_model_name_or_path": "google/gemma-4-E4B-it",
"bias": "none",
"fan_in_fan_out": false,
"inference_mode": true,
"init_lora_weights": true,
"lora_alpha": 32,
"lora_dropout": 0.05,
"modules_to_save": null,
"peft_type": "LORA",
"r": 64,
"target_modules": "all-linear",
"task_type": "CAUSAL_LM",
"training_step": 656
} |